For the analysis of a time-to-event (T2E) endpoint in a single-arm (SAT) or randomized clinical trial (RCT) it is generally perceived that interpretation of a given estimate of the survival function, or the comparison between two groups, hinges on some quantification of the amount of follow-up. Typically, a median of some loosely defined quantity is reported. However, as already discussed in Shuster in 1991, whatever median is reported is typically not answering the question(s) trialists actually have in terms of follow-up quantification. This talk will focus on the following discussion points: (1) The estimand framework put forward in the ICH E9 estimand addendum has been broadly implemented in pharmaceutical drug development, so far primarily for efficacy endpoints. We have found that taking inspiration from the estimand framework to structure the question of follow-up for a T2E endpoint and all the quantities that have been proposed to estimate it allows for a transparent way of describing and appreciating the various approaches. (2) Following the thinking process in the addendum we formulate a comprehensive list of relevant scientific questions that trialists have when reporting T2E data and which are often answered with reference to some unclearly defined quantifier of follow-up. We illustrate how instead these questions should be answered, and that reference to an unclearly defined follow-up quantity is not necessary. (3) The literature so far has focused on quantifying follow-up for estimation of a survival function in one group. However, in oncology drug development key decisions are made based on RCTs, and we discuss relevant scientific questions in this context. (4) Although our conclusion will be that generally used follow-up quantifiers are not useful, we define and illustrate follow-up quantifiers, some of which have not been discussed in the statistical literature so far but are routinely used in reporting of trials. Finally, with the advent of immunotherapies in oncology patterns of survival functions in RCT emerged, e.g. delayed separation, that may require different thinking on some of the relevant scientific questions.